Focused On-demand Library for GDNF-inducible zinc finger protein 1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

We utilise our cutting-edge, exclusive workflow to develop focused libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.







Alternative names:

Zinc finger and BTB domain-containing protein 23; Zinc finger protein 336

Alternative UPACC:

Q9H116; A8K199; B2RBC3; B3KPL4; B4DF58; D3DW39; Q54A22; Q96N08; Q9BQK9; Q9H117; Q9H6W6


GDNF-inducible zinc finger protein 1, also known as Zinc finger and BTB domain-containing protein 23 or Zinc finger protein 336, plays a crucial role as a transcriptional repressor. It specifically binds the GZF1 responsive element, potentially regulating VSX2/HOX10 expression. This protein's involvement in cellular processes underscores its importance in gene expression regulation.

Therapeutic significance:

The protein is linked to an autosomal recessive disease characterized by joint laxity, short stature, and severe myopia, highlighting its clinical relevance. Understanding the role of GDNF-inducible zinc finger protein 1 could open doors to potential therapeutic strategies for managing and treating this condition.

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